Adversarial and Random Transformations for Robust Domain Adaptation and Generalization

Data augmentation has been widely used to improve generalization in training deep neural networks. Recent works show that using worst-case transformations or adversarial augmentation strategies can significantly improve accuracy and robustness. However, due to the non-differentiable properties of im...

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Detalles Bibliográficos
Autores principales: Xiao, Liang, Xu, Jiaolong, Zhao, Dawei, Shang, Erke, Zhu, Qi, Dai, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256093/
https://www.ncbi.nlm.nih.gov/pubmed/37300000
http://dx.doi.org/10.3390/s23115273

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256093/
https://www.ncbi.nlm.nih.gov/pubmed/37300000
http://dx.doi.org/10.3390/s23115273

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